Reconstructing Three-decade Global Fine-Grained Nighttime Light Observations by a New Super-Resolution Framework

Satellite-collected nighttime light provides a unique perspective on human activities, including urbanization, population growth, and epidemics. Yet, long-term and fine-grained nighttime light observations are lacking, leaving the analysis and applications of decades of light changes in urban facilities undeveloped. To fill this gap, we developed an innovative framework and used it to design a new super-resolution model that reconstructs low-resolution nighttime light data into high resolution. The validation of one billion data points shows that the correlation coefficient of our model at the global scale reaches 0.873, which is significantly higher than that of other existing models (maximum = 0.713). Our model also outperforms existing models at the national and urban scales. Furthermore, through an inspection of airports and roads, only our model's image details can reveal the historical development of these facilities. We provide the long-term and fine-grained nighttime light observations to promote research on human activities. The dataset is available at \url{https://doi.org/10.5281/zenodo.7859205}

Artificially lit surface of Earth at night increasing in radiance and extent

This is the author accepted manuscript. The final version is available from AAAS via the DOI in this record.A central aim of the “lighting revolution” (the transition to solid-state lighting technology) is decreased energy consumption. This could be undermined by a rebound effect of increased use in response to lowered cost of light. We use the first-ever calibrated satellite radiometer designed for night lights to show that from 2012 to 2016, Earth’s artificially lit outdoor area grew by 2.2% per year, with a total radiance growth of 1.8% per year. Continuously lit areas brightened at a rate of 2.2% per year. Large differences in national growth rates were observed, with lighting remaining stable or decreasing in only a few countries. These data are not consistent with global scale energy reductions but rather indicate increased light pollution, with corresponding negative consequences for flora, fauna, and human well-being.This article is based upon work from COST Action ES1204 LoNNe, supported by COST (European Cooperation in Science and Technology). The authors acknowledge the funding received by ERA-PLANET (www.era-planet.eu) funded by the EC as part of H2020 (contract no. 689443). NOAA’s participation was funded by NASA’s VIIRS science program, contract number NNH15AZ01I. ASM’s contribution was funded by ORISON project (H2020-INFRASUPP-2015-2) Cities at Night

Calibration and analysis of the uncertainty in downscaling global land use and land cover projections from GCAM using Demeter (v1.0.0)

Demeter is a community spatial downscaling model that disaggregates land use and land cover changes projected by integrated human–Earth system models. Demeter has not been intensively calibrated, and we still lack good knowledge about its sensitivity to key parameters and parameter uncertainties. We used long-term global satellite-based land cover records to calibrate key Demeter parameters. The results identified the optimal parameter values and showed that the parameterization substantially improved the model's performance. The parameters of intensification ratio and selection threshold were the most sensitive and needed to be carefully tuned, especially for regional applications. Further, small parameter uncertainties after calibration can be inflated when propagated into future scenarios, suggesting that users should consider the parameterization equifinality to better account for the uncertainties in Demeter-downscaled products. Our study provides a key reference for Demeter users and ultimately contributes to reducing the uncertainties in Earth system model simulations.</p

Картирование ВВП и ППС на субнациональном уровне на основе спутниковых снимков территории стран Восточной Европы и СНГ

Following the line of research, originated from the paper by Henderson et al. (2012), this article focuses on how "observations from the above", in the form of night-lights satellite data, might contribute in mapping at very fine geographical level (ideally, one square km), two core macroeconomic indicators used extensively in the Sustainable Development Goals monitoring and reporting framework: Gross Domestic Product (GDP) and Purchasing Power Parities (PPPs). Recent empirical economic studies have paid increasing attention on the association between night-lights observations and economic growth, in order to estimate a consistent and objective level of economic activities at subnational level. In the present paper, analyses are carried out on a panel of 17 Eastern Europe and CIS countries for the period 2000-2013 and use is made of indicators constructed from satellite images in the form of night lights, as processed by the US Department of Defense, and its Defense Meteorological Satellite Program's OperationalLinescan System. Estimations of GDP in current US dollars and PPP terms are carried out at both national and sub-national level, and results are compared with the official available information. Estimates of GDP and PPP were also compared, at national level, with those in the World Bank data-set, showing similar behaviours. Results are used to obtain gridded maps of GDPs and PPPs

Assessment of Night-Time Lighting for Global Terrestrial Protected and Wilderness Areas

Protected areas (PAs) play an important role in biodiversity conservation and ecosystem integrity. However, human development has threatened and affected the function and effectiveness of PAs. The Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) night-time stable light (NTL) data have proven to be an effective indicator of the intensity and change of human-induced urban development over a long time span and at a larger spatial scale. We used the NTL data from 1992 to 2013 to characterize the human-induced urban development and studied the spatial and temporal variation of the NTL of global terrestrial PAs. We selected seven types of PAs defined by the International Union for Conversation of Nature (IUCN), including strict nature reserve (Ia), wilderness area (Ib), national park (II), natural monument or feature (III), habitat/species management area (IV), protected landscape/seascape (V), and protected area with sustainable use of natural resources (VI). We evaluated the NTL digital number (DN) in PAs and their surrounding buffer zones, i.e., 0–1 km, 1–5 km, 5–10 km, 10–25 km, 25–50 km, and 50–100 km. The results revealed the level, growth rate, trend, and distribution pattern of NTL in PAs. Within PAs, areas of types V and Ib had the highest and lowest NTL levels, respectively. In the surrounding 1–100 km buffer zones, type V PAs also had the highest NTL level, but type VI PAs had the lowest NTL level. The NTL level in the areas surrounding PAs was higher than that within PAs. Types Ia and III PAs showed the highest and lowest NTL growth rate from 1992 to 2013, respectively, both inside and outside of PAs. The NTL distributions surrounding the Ib and VI PAs were different from other types. The areas close to Ib and VI boundaries, i.e., in the 0–25 km buffer zones, showed lower NTL levels, for which the highest NTL level was observed within the 25–100 km buffer zone. However, other types of PAs showed the opposite NTL patterns. The NTL level was lower in the distant buffer zones, and the lowest night light was within the 1–25 km buffer zones. Globally, 6.9% of PAs are being affected by NTL. Conditions of wilderness areas, e.g., high latitude regions, Tibetan Plateau, Amazon, and Caribbean, are the least affected by NTL. The PAs in Europe, Asia, and North America are more affected by NTL than South America, Africa, and Oceania

Desastres naturales y crecimiento económico: Evidencia para distritos de Argentina

Los desastres naturales representan una seria amenaza a nivel global. Este trabajo avanza en la estimación del impacto que los desastres naturales generan sobre el crecimiento económico. En particular, se analiza el caso de los distritos argentinos para el período 1992-2013. Debido a la falta de datos desagregados de PBI, se utilizan mapas de luminosidad nocturna -como proxy de la actividad económica y el crecimiento- según lo reportado por la Administración Nacional Oceánica y Atmosférica (NOAA). La información sobre desastres proviene de los registros del Sistema de Inventario de Desastres (DesInventar). Se implementa un análisis de regresión considerando un panel de 350 distritos durante más de dos décadas. Se encuentra que, un desastre natural adicional, ajustado por severidad, se asocia con una reducción del 0.53% en el crecimiento económico en el año de su ocurrencia. Los desastres geofísicos e hidrológicos son los responsables de este efecto negativo. No hay evidencia de efectos persistentes sobre el crecimiento. Los hallazgos son especialmente relevantes considerando que se espera un aumento en la frecuencia e intensidad de los desastres, a futuro, como resultado del cambio climático, y que los países en desarrollo son más vulnerables ante desastres.Fil: González, Fernando Antonio Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; ArgentinaFil: Santos, Maria Emma. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; ArgentinaFil: London, Silvia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; Argentin

A Stepwise Calibration of Global DMSP/OLS Stable Nighttime Light Data (1992–2013)

The Defense Meteorological Satellite Program (DMSP)/Operational Linescan System (OLS) stable nighttime light (NTL) data provide a wide range of potentials for studying global and regional dynamics, such as urban sprawl and electricity consumption. However, due to the lack of on-board calibration, it requires inter-annual calibration for these practical applications. In this study, we proposed a stepwise calibration approach to generate a temporally consistent NTL time series from 1992 to 2013. First, the temporal inconsistencies in the original NTL time series were identified. Then, a stepwise calibration scheme was developed to systematically improve the over- and under- estimation of NTL images derived from particular satellites and years, by making full use of the temporally neighbored image as a reference for calibration. After the stepwise calibration, the raw NTL series were improved with a temporally more consistent trend. Meanwhile, the magnitude of the global sum of NTL is maximally maintained in our results, as compared to the raw data, which outperforms previous conventional calibration approaches. The normalized difference index indicates that our approach can achieve a good agreement between two satellites in the same year. In addition, the analysis between the calibrated NTL time series and other socioeconomic indicators (e.g., gross domestic product and electricity consumption) confirms the good performance of the proposed stepwise calibration. The calibrated NTL time series can serve as useful inputs for NTL related dynamic studies, such as global urban extent change and energy consumption

Micro and Macro Indexes of Economic Activity: Multiple Indicators and Multiple Methods Using Bangladesh as a Test Case

The first chapter explores, the use of night-time lights as a proxy for estimating annual GDP per capita and subsequently the GDP per capita growth rate. It is observed that even though, Bangladesh’s, GDP per capita is under-estimated, the annual growth rate is over-estimated. The second chapter explores the quality of the household surveys conducted in Bangladesh through the application of the Benford’s Law and triangulation against administrative data. Sampling errors are detected in all rounds of the household surveys. The results showed that the micro dataset over-sampled wealthier households. This indicated that the income and expenditure levels of the three lowest quartiles, estimated from the household surveys, is likely over-estimated. The results of the first two chapters are then combined to comment on the state of inequality in Bangladesh. It is observed that GDP per capita is higher than expected, while the income of the lowest three income quartiles is lower than estimated. Thus, true inequality is likely to be much higher than what is indicated by the published Gini-coefficients. The fourth chapter assesses the accuracy of a proxy-means test, the Poverty Probability Index, in classifying household poverty, in the absence of sound data. Applicability of the PPI, over years and across population sub-groups, was tested. It was seen that the index overestimated poverty probability in both cases. In the last chapter, machine learning algorithms are used to develop alternatives to the Poverty Probability Index, in the absence of extensive domain knowledge. These models out-performed the PPI by 3 percentage points in terms of accuracy and ROC-AUC

Nighttime Lights as a Proxy for Economic Performance of Regions

Studying and managing regional economic development in the current globalization era demands prompt, reliable, and comparable estimates for a region’s economic performance. Night-time lights (NTL) emitted from residential areas, entertainment places, industrial facilities, etc., and captured by satellites have become an increasingly recognized proxy for on-ground human activities. Compared to traditional indicators supplied by statistical offices, NTLs may have several advantages. First, NTL data are available all over the world, providing researchers and official bodies with the opportunity to obtain estimates even for regions with extremely poor reporting practices. Second, in contrast to non-standardized traditional reporting procedures, the unified NTL data remove the problem of inter-regional comparability. Finally, NTL data are currently globally available on a daily basis, which makes it possible to obtain these estimates promptly. In this book, we provide the reader with the contributions demonstrating the potential and efficiency of using NTL data as a proxy for the performance of regions